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Bayesian Vars: A Survey of the Recent Literature with An Application to the European Monetary System

  • Matteo Ciccarelli
  • Alessandro Rebucci

This paper reviews recent advances in the specification and estimation of Bayesian Vector Autoregressive models (BVARs). After describing the Bayesian principle of estimation, we first present the methodology originally developed by Litterman (1986) and Doan et al. (1984) and review alternative priors. We then discuss extensions of the basic model and address issues in forecasting and structural analysis. An application to the estimation of a system of time-varying reaction functions for four European central banks under the European Monetary System (EMS) illustrates how some of the results previously presented may be applied in practice.

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Paper provided by International Monetary Fund in its series IMF Working Papers with number 03/102.

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Length: 44
Date of creation: 01 May 2003
Date of revision:
Handle: RePEc:imf:imfwpa:03/102
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  1. Bernanke, Ben S. & Mihov, Ilian, 1997. "What does the Bundesbank target?," European Economic Review, Elsevier, vol. 41(6), pages 1025-1053, June.
  2. Matteo Ciccarelli & Alessandro Rebucci, 2001. "The Transmission Mechanism of European Monetary Policy: Is There Heterogeneity? Is It Changing Over Time?," Banco de Espa�a Working Papers 0115, Banco de Espa�a.
  3. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-52, September.
  4. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
  5. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
  6. Clarida, Richard & Gali, Jordi & Gertler, Mark, 1997. "Monetary Policy Rules in Practice: Some International Evidence," Working Papers 97-32, C.V. Starr Center for Applied Economics, New York University.
  7. Canova, Fabio & Ciccarelli, Matteo, 2001. "Forecasting and Turning Point Predictions in a Bayesian Panel VAR Model," CEPR Discussion Papers 2961, C.E.P.R. Discussion Papers.
  8. Kim, C-J., 1991. "Dynamic Linear Models with Markov-Switching," Papers 91-8, York (Canada) - Department of Economics.
  9. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
  10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  11. Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," Working Paper 96-13, Federal Reserve Bank of Atlanta.
  12. Zha, Tao, 1999. "Block recursion and structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 90(2), pages 291-316, June.
  13. Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," SSE/EFI Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
  14. Luis J. Álvarez & Fernando C. Ballabriga, 1994. "BVAR models in the context of cointegration: A Monte Carlo experiment," Banco de Espa�a Working Papers 9405, Banco de Espa�a.
  15. Koop, G, 1992. "Aggregate Shocks and Macroeconomic Fluctuations: A Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(4), pages 395-411, Oct.-Dec..
  16. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
  17. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
  18. repec:cup:cbooks:9780521558839 is not listed on IDEAS
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